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Aerospike

High-performance NoSQL database for real-time processing

Senior Forward Deployed Engineer - Operational AI

AI Application Engineering +1Posted on Nov 11
Full-timeLondon, UKIn-person

About the Job

Requirements

  • Bring 5–8+ years of hands-on software development experience building and deploying backend services, distributed systems, or high-throughput data platforms in production.
  • Be fluent in at least one modern systems or backend language: Go, Java, Python, or C/C++, with solid fundamentals in concurrency, API design, and asynchronous patterns.
  • Have practical experience working with low-latency key-value stores, distributed databases, or streaming data platforms such as Kafka, Redis, Cassandra, or Aerospike.
  • Have hands-on experience building services that interface with large language models, retrieval-augmented generation architectures, vector databases, or agent frameworks such as LangChain, LlamaIndex, or Temporal.
  • Have experience implementing authentication and authorization, including OAuth and role-based or attribute-based access control, data validation, and auditable logging in sensitive environments.
  • Be able to navigate ambiguous requirements, communicate technical trade-offs to customer engineers, and work independently with minimal oversight.

Responsibilities

  • Build and deploy real-time distributed data models for agent, session, and workflow state, supporting high-concurrency reads and writes while meeting freshness, consistency, and failover recovery requirements.
  • Implement pipelines joining transactional data, streaming sources, vector search indexes, and graph relationships so agent workflows make decisions using real-time, permission-aware context.
  • Integrate policy checks, authentication and authorization boundaries, execution governors, and human-in-the-loop review steps into real-time application paths.
  • Build logging and tracing hooks that record context snapshots, decisions, tool execution, and state mutations to meet enterprise compliance and security standards.
  • Connect and automate operational execution flows from state to context, action, mutation, and updated state, ensuring downstream results reliably inform the next cycle.
  • Work alongside client engineers to translate operational challenges and specifications into technical designs, integration plans, and verifiable delivery milestones.
  • Implement scalable services and integrations across Aerospike, enterprise data systems, vector engines, and agent orchestration frameworks.
  • Own technical validation through launch by debugging distributed systems issues, profiling bottlenecks, and ensuring systems operate reliably under high traffic.
  • Test real-world operational characteristics, including p99 latency, throughput, cache invalidation, context freshness, failure recovery, and policy enforcement, beyond basic model benchmarks.
  • Identify recurring customer requirements and feed them back into internal engineering to create reusable starter kits, SDK wrappers, test fixtures, and documentation.
  • Partner with Product, Core Engineering, and Solutions teams to resolve platform bugs, close functional gaps, and assist client teams with deployment best practices.
  • Lead technical integration, custom data modeling, and application code for production Operational AI implementations; routine account administration, ticket escalation, and generic maintenance support are not the role's responsibility.

Desired Qualifications

  • Have hands-on experience with the Aerospike Real-time Data Platform, Aerospike Vector Search, or Aerospike Graph.
  • Have experience with distributed task queues, checkpointing, or durable workflow engines such as Temporal or Airflow.
  • Have a background in containerized deployments using Docker or Kubernetes and cloud environments such as AWS, GCP, or Azure.
  • Be familiar with distributed tracing tools such as OpenTelemetry, Prometheus, or Jaeger.

About the Company

Aerospike

High-performance NoSQL database for real-time processing

Aerospike builds high-performance, scalable NoSQL databases for real-time applications. Its core product is a NoSQL database optimized for speed and low latency, capable of millions of transactions per second, with deployments on-premises, in the cloud, or in hybrid environments, and support for Kubernetes and Docker. It distinguishes itself by delivering real-time, high-throughput data processing at scale with features like cross-datacenter replication, strong consistency, and active-active deployments for enterprise use. The company aims to provide fast, reliable access to large volumes of data for mission-critical applications in real time.

Company size
201-500
Company stage
Late Stage VC
Total funding
$271M
Headquarters
Mountain View, CA
Founded
2009

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